Aligning Artificial Intelligence with Organizational Contexts

Artificial Intelligence (AI) offers enormous potential for tackling challenges such as staffing shortages and a growing elderly population with increasing healthcare needs. However, effectively embedding AI in organizations is a complex sociotechnical endeavor; if misaligned, it can lead to knowledge loss or employee dissatisfaction. This dissertation systematically examines the key components of AI alignment. Four studies—two at a general level and two focused on Natural Language Processing (NLP) in clinical settings—explore how AI can best be harmonized with organizational requirements. The resulting framework supports researchers and practitioners alike in planning, integrating, and continuously refining AI solutions. Moreover, this work opens new horizons in research and practice by examining AI in specific contexts and identifying aspects that have received little attention thus far.